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A new hybrid algorithm is introduced into solving job shop scheduling problems, which combines knowledge evolution algorithm(KEA) and particle swarm optimization(PSO) algorithm. By the mechanism of KEA, its global search ability is fully utilized for finding the global solution. By the operating characteristic of PSO, the local search ability is also made full use. Through the combination, better...
Resource allocation in grid environment is a complex undertaking due to the heterogeneity and dynamic nature aroused by wide area sharing. Most of the existing studies for this problem have been found to be performance deficiency or slow convergence. To address the heterogeneous and computationally intractable problem of resource allocation optimization in grid, this paper presents an allocation algorithm...
This paper proposes improvements to PSO with velocity clamping to overcome its known disadvantage of allowing particle to move outside the search space. The new proposed PSO algorithm actively penalizes the particle velocities to ensure particles are confined within the search space. The algorithm is called PSO with active velocity penalty (PSO-AVP). The paper also presents some simulation results...
Attribute reduction is one of the important topics in the research on rough set theory. In confrontation with dynamic data, common methods of attributes reduction have such disadvantages as unstable reduction results, intensive computation and the difficulty in meeting the need of real-time processing. To solve these problems, a method of dynamic attributes reduction with improved PSO algorithm is...
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